Advanced data structures is a core course in Computer Science which most graduate program in Computer Science, Computer Science and Engineering, and other allied engineering disciplines, offer during the first year or first semester of the curriculum. The objective of this course is to enable students to have the much-needed foundation for advanced technical skill, leading to better problem-solving in their respective disciplines. Although the course is running in almost all the technical universities for decades, major changes in the syllabus have been observed due to the recent paradigm shift of computation which is more focused on huge data and internet-based technologies. Majority of the institute has been redefined their course content of advanced data structure to fit the current need and course material heavily relies on research papers because of nonavailability of the redefined text book advanced data structure. To the best of our knowledge well-known textbook on advanced data structure provides only partial coverage of the syllabus.
The book offers comprehensive coverage of the most essential topics, including:
- Part I details advancements on basic data structures, viz., cuckoo hashing, skip list, tango tree and Fibonacci heaps and index files.
- Part II details data structures of different evolving data domains like special data structures, temporal data structures, external memory data structures, distributed and streaming data structures.
- Part III elucidates the applications of these data structures on different areas of computer science viz, network, www, DBMS, cryptography, graphics to name a few. The concepts and techniques behind each data structure and their applications have been explained.
- Every chapter includes a variety of Illustrative Problems pertaining to the data structure(s) detailed, a summary of the technical content of the chapter and a list of Review Questions, to reinforce the comprehension of the concepts.
The book could be used both as an introductory or an advanced-level textbook for the advanced undergraduate, graduate and research programmes which offer advanced data structures as a core or an elective course. While the book is primarily meant to serve as a course material for use in the classroom, it could be used as a starting point for the beginner researcher of a specific domain.
Table of Contents
I Part One: Theoretical Advancements. Introduction. O(1) Search by Hashing. O(log(n)) ordered search (Trees & Lists). Find set, find min & find word. II Part Two: Evolving Paradigms. Evolving paradigms of data structures. Spatial Data Structures. Temporal Data Structures. External Memory Data Structures. Distributed Data Structure. Synopsis Data Structures. III Part Three: Recent Applications. Introduction to applications. Application to Cryptography. Application to IR and WWW. Application to Data science. Application to Network and IOT. Application to System. Application to Database. Application to Image and Graphics. IV Bibliography and Index. Bibliography. First index. Second index.
Dr. Suman Saha had spent the last 14 years developing as a scientist in the recent research areas of Data and information science covering information retrieval, web mining, decision theory, social network analysis and big data technologies. He started his research in the field of web mining as a senior research scientist in the “Center for Soft Computing Research: A National Facility”, Indian Statistical Institute, Kolkata, India for a duration of almost five years. After that his research continued as Assistant Professor in the dept. of computer science, Jaypee University of Information Technology, Himachal, India in addition to the teaching and other departmental responsibilities for last eight years. He obtained his PhD from Jaypee University of Information Technology preceded by M.Tech in computer science, from Indian Statistical Institute and M.Sc. in Mathematics, from University of Calcutta. His thesis title is “Community Detection in Complex Network: Metric Space, Nearest Neighbor Search, Low-Rank Approximation and Optimality” During his last eight years stay at Jaypee University of Information Technology as assistant professor he had taught various courses like advanced web mining, cloud computing, advanced algorithm, fundamentals of algorithm, advanced data structure and many others. He is supervising 2 PhD students and guided around 15 master thesis as well as around 50 bachelor thesis.
Dr. Shailendra Shukla has completed “MS-(Information Security)” from “Indian Institute of Information Technology Allahabad”, and then completed PhD from “Indian Institute of Technology Patna” in computer science. His doctorial work is based on “On Boundary Detection and Localization in Wireless Sensor Networks”. In this work he proposed a collection of networking algorithms which addresses the security problems like routing in Internet of Things, localization, boundary node detection (surveillance), virtual coordinate assignment (Geography routing/localizations), cyber physical systems, monitoring and surveillance. He has published articles in various publication houses like in Elsevier, Springer, IEEE. Currently he is working as an assistant professor at Jaypee University Waknaghat. He is supervising 2 PhD students and guided 5 master student.